Neuroplasticity: The Brain's Ability to Reorganize
Definition
Neuroplasticity
The brain’s ability to reorganize itself by forming and strengthening new neural connections.
- This adaptability allows the brain to:
- Recover from injuries.
- Adapt to new experiences.
- Learn new skills.
How Neuroplasticity Works
- When you learn something new, your brain forms new synapses, the connections between neurons.
- With repeated practice, these connections strengthen, making the skill easier to perform.
- If you stop practicing, the connections weaken and may eventually disappear.
- This process is called neural pruning.
When asked to explain neuroplasticity, always include both synapse formationandpruning in your answer.
Analogy- Think of neuroplasticity as rerouting a GPS.
- When a road is blocked, new routes are created to reach the destination.
- Similarly, the brain forms new pathways to adapt to changes or recover from damage.
Key Studies on Neuroplasticity
Maguire et al. (2000): London Taxi Drivers
Case study- Aim:
- To investigate whether the brains of London taxi drivers would show structural changes as a result of extensive spatial navigation experience.
- Method
- Participants: 16 right-handed male London taxi drivers (average experience: 14 years).
- Control group: 50 right-handed males who were not taxi drivers.
- Procedure: MRI scans were taken of all participants.
- Design: Quasi-experiment (naturally occurring IV = taxi driver vs. non-driver; DV = hippocampal volume).
- Analysis: Voxel-based morphometry (VBM) and pixel-counting techniques were used to measure grey matter volume in the hippocampus.
- Findings
- Taxi drivers had significantly larger posterior hippocampi compared to controls.
- Control participants had larger anterior hippocampi.
- Correlation found
- The longer a person had been a taxi driver, the larger the posterior hippocampus volume.
- Conclusion
- The hippocampus is involved in spatial memory and navigation.
- Extensive practice of navigation (environmental demand) is associated with structural changes in the brain → evidence of neuroplasticity.
- Why this study is strong
- Supports neuroplasticity: Shows the brain can adapt structurally to environmental demands.
- Methodological strength: MRI scans give objective, measurable data.
- Ecological validity: Real-world task (navigation), not artificial lab learning.
- Limitations
- Quasi-experiment: Cannot prove causation; taxi drivers may have had larger hippocampi before training.
- Sample bias: All male, right-handed, small sample. Findings may not generalize.
- Correlational data: Length of time as a driver correlates with hippocampal size, but other lifestyle factors could contribute.
- Maguire is a classic example of quasi-experimental research.
- You can use it to support questions on both neuroplasticity and localization of function.
Draganski et al. (2004): Juggling Study
Case study- Aim
- To investigate whether learning a new motor skill (juggling) would cause structural and functional changes in the brain.
- Method
- Participants: 24 volunteers with no prior juggling experience.
- Design: Longitudinal experimental design with control group.
- Procedure:
- MRI scans were taken before learning (baseline).
- Experimental group practiced juggling for 3 months.
- Second MRI scans were conducted after the 3 months of practice.
- Participants then stopped juggling for 3 months.
- Final MRI scans were taken after this non-practice period.
- Control group: Did not learn juggling but were scanned at the same intervals.
- Findings
- Initial scan (baseline): No structural differences between groups.
- After 3 months of juggling: The experimental group showed increased grey matter in the mid-temporal area of the cortex (associated with visual and motor skill learning).
- After 6 months (no juggling): Grey matter in these areas decreased, though it remained slightly higher than baseline.
- Conclusion
- Learning a new skill (juggling) induces structural changes in the brain, evidence of neuroplasticity.
- These changes are temporary and experience-dependent; without practice, connections weaken due to neural pruning.
- Why this study is strong
- Causal evidence: Experimental design allows stronger inference than correlational studies like Maguire.
- Objective measurement: MRI scans provide clear, replicable biological evidence.
- Supports experience-dependent plasticity: Shows the brain adapts in response to learning.
- Limitations
- Small sample size → may reduce reliability and generalisability.
- Low ecological validity: Juggling is an artificial task, not representative of everyday motor learning.
- Short-term focus: Only measured for 6 months; long-term persistence of brain changes unclear.
- In SAQs: Define neuroplasticity → outline Draganski with emphasis on causal evidence (longitudinal experimental).
- In ERQs: Use Draganski alongside Maguire (2000) to contrast experience-dependent plasticity (learning a skill) vs. long-term environmental adaptation (navigation).
